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/*
    Appellation: sigmoid <mod>
    Contrib: FL03 <jo3mccain@icloud.com>
*/
use ndarray::*;
use num::complex::ComplexFloat;
use num::{Float, Zero};

pub fn relu<T>(args: &T) -> T
where
    T: Clone + PartialOrd + Zero,
{
    if args > &T::zero() {
        return args.clone();
    }
    T::zero()
}

pub fn sigmoid<T>(args: &T) -> T
where
    T: ComplexFloat,
{
    (T::one() + (*args).neg().exp()).recip()
}

pub fn softmax<T, D>(args: &Array<T, D>) -> Array<T, D>
where
    D: Dimension,
    T: Float,
{
    let denom = args.mapv(|x| x.exp()).sum();
    args.mapv(|x| x.exp() / denom)
}

pub fn softmax_axis<T, D>(args: &Array<T, D>, axis: Option<usize>) -> Array<T, D>
where
    D: Dimension + RemoveAxis,
    T: NdFloat,
{
    let exp = args.mapv(|x| x.exp());
    if let Some(axis) = axis {
        let denom = exp.sum_axis(Axis(axis));
        exp / denom
    } else {
        let denom = exp.sum();
        exp / denom
    }
}

pub fn tanh<T>(args: &T) -> T
where
    T: ComplexFloat,
{
    args.tanh()
}

build_unary_trait!(ReLU.relu, Sigmoid.sigmoid, Softmax.softmax, Tanh.tanh,);

/*
 ********** Implementations **********
*/
macro_rules! nonlinear {
    ($($rho:ident<$($T:ty),* $(,)?>::$call:ident),* $(,)? ) => {
        $(
            nonlinear!(@loop $rho<$($T),*>::$call);
        )*
    };
    (@loop $rho:ident<$($T:ty),* $(,)?>::$call:ident ) => {
        $(
            nonlinear!(@impl $rho<$T>::$call);
        )*

        nonlinear!(@arr $rho::$call);
    };
    (@impl $rho:ident<$T:ty>::$call:ident) => {
        impl $rho for $T {
            type Output = $T;

            fn $call(&self) -> Self::Output {
                $call(self)
            }
        }

        impl<'a> $rho for &'a $T {
            type Output = $T;

            fn $call(&self) -> Self::Output {
                $call(*self)
            }
        }

    };
    (@arr $name:ident::$call:ident) => {
        impl<A, S, D> $name for ArrayBase<S, D>
        where
            A: Clone + $name,
            D: Dimension,
            S: Data<Elem = A>
        {
            type Output = Array<<A as $name>::Output, D>;

            fn $call(&self) -> Self::Output {
                self.map($name::$call)
            }
        }
    };

}

nonlinear!(
    ReLU < f32,
    f64,
    i8,
    i16,
    i32,
    i64,
    i128,
    isize,
    u8,
    u16,
    u32,
    u64,
    u128,
    usize > ::relu,
    Sigmoid < f32,
    f64,
    num::Complex<f32>,
    num::Complex < f64 >> ::sigmoid,
    Tanh < f32,
    f64,
    num::Complex<f32>,
    num::Complex < f64 >> ::tanh,
);